文章基本信息

标题：Implementing Ant Colony Optimization for Test Case Selection and Prioritization
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作者：Bharti Suri ; Shweta Singhal
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2011
卷号：3
期号：05
页码：1924-1932
出版社：Engg Journals Publications
摘要：Regression Testing is an inevitable and a very costly activity to be performed, often in a time and resource constrained environment. Thus we use techniques like Test Case Selection and Prioritization, to select and prioritize a subset from the complete test suite, fulfilling some chosen criteria. Ant Colony Optimization (ACO) is a technique based on the real life behavior of ants. This paper presents an implementation of an already introduced Ant Colony Optimization Algorithm for Test Case Selection and Prioritization. Graph representation and example runs explained in the paper show how the random nature of ACO helps to explore the possible paths and choose the optimal from them. Results show that ACO leads to solutions that are in close proximity with optimal solutions.
关键词：Regression Testing; Ant Colony Optimization; Implementation; Test Case Selection; Test Case Prioritization